With the tools we have today, we can do even more to close the gap in how we assess risk.

Imagine you want to join a pickup soccer game, what we call a chamusca in Guatemala, but the team captain tells you that only people who have played before can join. The obvious question is: how do you play your first game if nobody will let you onto the team?

Now replace “pickup soccer” with “credit.”

For decades, the absence of a credit history has been treated as a sign of high risk or a reason for distrust. And that made sense: credit history was the most reliable and readily available information for understanding a customer’s repayment behavior. But often, having no history means something much simpler: nobody has given you a chance to get started.

The numbers bear this out. In Guatemala, about 70% of the economically active population works in the informal economy, according to the National Statistics Institute (INE, 2025). And according to the 2025 National Household Financial Inclusion Survey (ENIFH), the country’s first nationally representative survey on this subject, just 42% of adults have at least one formal financial product or service. Put another way, roughly 58% of Guatemalans are outside the system. The gap is wider in rural areas and western Guatemala, where access falls below 20% in administrative regions such as Huehuetenango.

We are talking about people who run small businesses, pay their suppliers on time, support their families, and make financial decisions every day without having a single formal financial product. Does that make them “risky customers”?

The same survey reveals something even more interesting: about 26% of the population has credit from sources outside financial institutions (ENIFH–INE, 2025). That includes advances from employers and loans from pawnshops, relatives, or friends. Demand for financing exists and is being met every day, but outside the system, without a formal record, at higher costs, and without any consumer protection. The system doesn’t see these people, yet they already function as borrowers.

Fortunately, technology is closing that gap and forcing us to question the logic of labeling people as “risks.” Today, we can understand someone’s financial behavior through alternative sources of information: the consistency of their sales and purchases, their business’s cash flow, utility payments, prepaid mobile top-ups, remittances (which eight out of ten recipient households still collect in cash), and transactions through digital wallets and local businesses acting as banking agents.

Used responsibly and with the customer’s consent, this data allows us to distinguish between someone who is simply unknown to the system and someone who actually poses a credit risk. Those are not the same thing, and confusing them carries an enormous economic and social cost.

A good risk assessment model should not aim to exclude as many people as possible. Quite the opposite. Its job is to assess the ability and willingness to repay using the best available evidence, not to penalize people for lacking a label. Every time we confuse a missing credit history with “high risk,” we shut out thousands of entrepreneurs and self-employed workers who could become excellent customers if we gave ourselves the chance to understand them instead of labeling them. And for financial institutions, this isn’t philanthropy. It is the largest market opportunity in front of us.

I am convinced that the risk lies not in the people themselves, but in the limited information we have chosen to use to assess them. Today, we have the tools to build a fuller picture. What is still missing is putting that data to work so we can take on that risk.

Column by Sergio Morales, General Manager of Vana+ and VP of Collections at Vana.